Category

Published on

12 Sep 2005

Abstract

Typical modeling and simulation efforts directed towards the
understanding of electron transport at the nanometer scale utilize
single workstations as computational engines. Growing understanding
of the involved physics and the need to model realistically extended
devices increases the complexity and size of the modeling and
simulation problems such that single CPU workstations can no longer
provide fast result turn-around times. Parallelization of scientific
and engineering oriented simulation codes can provide significant
computational speed-up, enable the study of larger more realistic
systems, and large-scale global optimization. Access to parallel
machines has up to about 7 years ago been limited to an elite few
people who were members of National Labs or participants in the
massively parallel Computational Science community. A typical
parallel computer has cost in the past several million dollars,
making them generally inaccessible to a large group of software
developers. The invention of Beowulf cluster computing around 1997
has spurred a dramatic revolution in the availability of parallel
computers in the scientific and engineering community. With a
relatively small investment of $50k-100k, which typically buys 32-64
CPUs, research groups all over the world have begun to utilize
cluster computers for their scientific and engineering endeavors.
This use of parallel computing will continue to increase in the
future, as CPU vendors are moving more and more to multi-core chip
designs. I would assume that in 5 years most computational
researchers will have a 16 or 32 CPU machine sitting under their
desk. Therefore I believe that parallel computing will be a key
element in the future of scientific modeling.

This seminar will review the principles of parallel code development
and the science of three different nanotechnology applications:
GENES (Genetically Engineered Nanoelectronic Structures - a genetic
algorithm-based optimization engironment), NEMO-3D (multimillion atom
electronic structure calculations), and NEMO-1D (the first
nanoelectronic engineering TCAD tool).

Bio

Gerhard Klimeck is the Technical Director of the Network for
Computational Nanotechnology at Purdue University and a Professor of
Electrical and Computer Engineering since Dec. 2003. He was the
Technical Group Supervisor for the Applied Cluster Computing
Technologies Group at the NASA Jet Propulsion Laboratory. His
research interest is in the modeling of nanoelectronic devices,
parallel cluster computing, genetic algorithms, and parallel image
processing. Gerhard developed the Nanoelectronic Modeling tool (NEMO
3-D) for multimillion atom simulations and continues to expand NEMO
1-D. Previously he was a member of technical staff at the Central
Research Lab of Texas Instruments where he served as manager and
principal architect of the Nanoelectronic Modeling (NEMO 1-D)
program. Dr. Klimeck received his Ph.D. in 1994 from Purdue
University and his German electrical engineering degree in 1990 from
Ruhr-University Bochum. Dr. Klimeck's work is documented in over 130
peer-reviewed publications and over 200 conference presentations. He
is a senior member of IEEE and member of APS, HKN and TBP. More
information about his work can be found at
http://ece.purdue.edu/~gekco

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